Design of output dv/dt filter for motor drives

Modern PWM inverter output voltage has high dv/dt, which causes problems such as voltage doubling that can lead to insulation failure, ground currents that results in electromagnetic interference concerns. The IGBT switching device used in such inverter are becoming faster, exacerbating these problems. This paper proposes a new procedure for designing the LC clamp filter. The filter increases the rise time of the output voltage of inverter, resulting in smaller dv/dt. In addition suitable selection of resonance frequency gives LCL filter configuration with improved attenuation. By adding this filter at output terminal of inverter which uses long cable, voltage doubling effect is reduced at the motor terminal. The design procedure is carried out in terms of the power converter based per unit scheme. This generalizes the design procedure to a wide range of power level and to study optimum designs. The effectiveness of the design is verified by computer simulation and experimental measurements.

Contrained linear spectral unmixing technique for regional land cover mapping using MODIS data

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up- to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat- TM/ETM+, IRS-1C/D LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (~ 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 m), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end- members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-III classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications.

Soft classification based Sub-pixel allocation model

Land cover (LC) refers to what is actually present on the ground and provide insights into the underlying solution for improving the conditions of many issues, from water pollution to sustainable economic development. One of the greatest challenges of modeling LC changes using remotely sensed (RS) data is of scale-resolution mismatch: that the spatial resolution of detail is less than what is required, and that this sub-pixel level heterogeneity is important but not readily knowable. However, many pixels consist of a mixture of multiple classes. The solution to mixed pixel problem typically centers on soft classification techniques that are used to estimate the proportion of a certain class within each pixel. However, the spatial distribution of these class components within the pixel remains unknown. This study investigates Orthogonal Subspace Projection - an unmixing technique and uses pixel-swapping algorithm for predicting the spatial distribution of LC at sub-pixel resolution. Both the algorithms are applied on many simulated and actual satellite images for validation. The accuracy on the simulated images is ~100%, while IRS LISS-III and MODIS data show accuracy of 76.6% and 73.02% respectively. This demonstrates the relevance of these techniques for applications such as urban-nonurban, forest-nonforest classification studies etc.

A Multi-layer Perceptron based Non-linear Mixture Model to estimate class abundance from mixed pixels

Sub-pixel classification is essential for the successful description of many land cover (LC) features with spatial resolution less than the size of the image pixels. A commonly used approach for sub-pixel classification is linear mixture models (LMM). Even though, LMM have shown acceptable results, pragmatically, linear mixtures do not exist. A non-linear mixture model, therefore, may better describe the resultant mixture spectra for endmember (pure pixel) distribution. In this paper, we propose a new methodology for inferring LC fractions by a process called automatic linear-nonlinear mixture model (AL-NLMM). AL-NLMM is a three step process where the endmembers are first derived from an automated algorithm. These endmembers are used by the LMM in the second step that provides abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual proportions are fed to multi-layer perceptron (MLP) architecture as input to train the neurons which further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. AL-NLMM is validated on computer simulated hyperspectral data of 200 bands. Validation of the output showed overall RMSE of 0.0089±0.0022 with LMM and 0.0030±0.0001 with the MLP based AL-NLMM, when compared to actual class proportions indicating that individual class abundances obtained from AL-NLMM are very close to the real observations.

A Low Power Frequency Multiplication Technique for Zigbee Transceiver

A low-power frequency multiplication technique, developed for ZigBee (IEEE 802.15.4) like applications is presented. We have provided an estimate for the power consumption for a given output voltage swing using our technique. The advantages and disadvantages which determine the application areas of the technique are discussed. The issues related to design, layout and process variation are also addressed. Finally, a design is presented for operation in 2.405-2.485-GHz band of ZigBee receiver. SpectreRF simulations show 30% improvement in efficiency for our circuit with regard to conversion of DC bias current to output amplitude, against a LC-VCO. To establish the low-power credentials, we have compared our circuit with an existing technique; our circuit performs better with just 1/3 of total current from supply, and uses one inductor as against three in the latter case. A test chip was implemented in UMC 0.13-mum RF process with spiral on-chip inductors and MIM (metal-insulator-metal) capacitor option.

Multi-physics self-consistent modeling in nanotechnological applications: quantum dots and quantum-well lasers

This paper reports a self-consistent Poisson-Schr¨odinger scheme including the effects of the piezoelectricity, the spontaneous polarization and the charge density on the electronic states and the quasi-Fermi level energy in wurtzite type semiconductor heterojunction and quantum-laser.

Some recent developments in solid state galvanic sensors

A critical revi<:w of the possibilities of measuring the ~artlal pressure of sulfur using solid state galvanic cells )'n;;cd on AgI, C" , B-alumina, CaO-Zr02' Na2S04-I and doped ;:":;, ,,,Ilil "Iltl ,,11: auxiliary "jectrodes are presentlOu. SOIll..., df tllc!iL' sYHtcmH h,}vu inherent limltntlol1$ when <:xl'o" ...d to environments contilining both oxygen and sulfur. Electrode polarization due to electronic conduction in the solid electrolyte is a significant factor limiting the ;lC'e,"'acy of isotlwrm:l1 cell",. The electrochemical flux of{lit' !'\)ndlwl Ill}: Ion LhnHO',h tht' ('!('ctrojyt(~ C:Ul },(,! llIinlnliz(,{j pfUjJL!f cell. dL:~) i.t',11. Noni!:iot.herm~ll cells \.Jlth temperaLure compensated reference electrodes have a number of advantages over thC'ir isothermal counterparts.

Continuous Recording of Retardation and Intensity of Echoes from the Ionosphere

Pulse retardation method of Breit and Tuve has been modified to record continuously the equivalent height as well as the intensity of reflections from the ionosphere. Synchronized pulses are transmitted, and the received ground pulse and the reflected pulses, after amplification and suitable distortion, are applied to the focusing cylinder of a cathode ray tube the horizontal deflecting plates of which are connected to a synchronized linear time base circuit. The pattern on the screen is composed of a bright straight line corresponding to the time base with dark gaps corresponding to the received pulses. The distance between the initial points of the gaps represents retardation while the widths of the gaps correspond to the intensity of the pulses. The pattern is photographed on a vertically moving film. One of the first few records taken at Bangalore on 4 megacycles is reproduced. It shows, among other things, that the less retarded component of magneto-ionic splitting from the F layer is present most of the time. Whenever the longer retardation component does occur, it has stronger intensity than the former. Towards the late evening hours, just before disappearing, when the F layer rises and exhibits magnetoionic splitting, the intensity of the less retarded component is extremely low compared with the other component.

Microwave cavity resonators. Some perturbation effects and their applications

Lagrange's equation is utilized to show the analogy of a lossless microwave cavity resonator with the conventional LC network. A brief discussion on the resonant frequencies of a microwave cavity resonator and the two degenerate companion modes H01 and E11 appearing in a cavity is given. The first order perturbation theory of a small deformation of the wall of a cavity is discussed. The effects of perturbation, such as the change in the resonant frequency and the Q of a cavity, the change in the electromagnetic field configurations and hence mixing of modes are also discussed. An expression for the coupling coefficient between the two degenerate modes H01 and E11 is derived with the help of the field equations. Results indicate that in the absence of perturbation the above two degenerate modes can co-exist without losing their individual identities. Several applications of the perturbation theory, such as the measurement of the dielectric properties of matter, study of ferromagnetic resonance, etc., are described.

Characterisation of Landscape with Forest Fragmentation Dynamics

Land cover (LC) and land use (LU) dynamics induced by human and natural processes play a major role in global as well as regional patterns of landscapes influencing biodiversity, hydrology, ecology and climate. Changes in LC features resulting in forest fragmentations have posed direct threats to biodiversity, endangering the sustainability of ecological goods and services. Habitat fragmentation is of added concern as the residual spatial patterns mitigate or exacerbate edge effects. LU dynamics are obtained by classifying temporal remotely sensed satellite imagery of different spatial and spectral resolutions. This paper reviews five different image classification algorithms using spatio-temporal data of a temperate watershed in Himachal Pradesh, India. Gaussian Maximum Likelihood classifier was found to be apt for analysing spatial pattern at regional scale based on accuracy assessment through error matrix and ROC (receiver operating characteristic) curves. The LU information thus derived was then used to assess spatial changes from temporal data using principal component analysis and correspondence analysis based image differencing. The forest area dynamics was further studied by analysing the different types of fragmentation through forest fragmentation models. The computed forest fragmentation and landscape metrics show a decline of interior intact forests with a substantial increase in patch forest during 1972-2007.

Sensitive Liquid Chromatography-Tandem Mass Spectrometry Method for the Determination of Olanzapine in Human Urine

A sensitive and selective liquid chromatographic-tandem mass spectrometric (LC-MS-MS) method was developed to determine olanzapine (OLZ) in human urine. After solid-phase extraction with SPE cartridge, the urine sample was analysed on a C-18 column (Symmetry 3.5 mu m, 50 x 4.6 mm i.d) interfaced with a triple quadrupole tandem mass spectrometer. Positive electrospray ionization was employed as the ionization source. The mobile phase consisted of ammonium acetate (pH 7.8)-acetonitrile (10:90, v/v). The method was linear over a concentration range of 1-100 ngml(-1). The lower limit of quantitation was 1 ngml(-1). The intra-day and inter-day relative standard deviation across three validation runs over the entire concentration range was < 11.5 %. The accuracy determined at three concentrations (8.0, 50.0 and 85.0 ngml(-1) OLZ) was within +/- 1.21 % in terms of relative errors.

A variant peptide of buffalo colostrum beta-lactoglobulin inhibits angiotensin I-converting enzyme activity

beta-lactoglobulin is a rich source of bioactive peptides. The LC-MS separated tryptic peptides of buffalo colostrum beta-lactoglobulin (BLG-col) were computed based on MS-MS fragmentation for de novo sequencing. Among the selected peptides (P1-P8), a variant was detected with methionine at position 74 instead of glutamate. The sequences of two peptides were identical to hypocholesterolemic peptides whereas the remaining peptides were in accordance with buffalo milk beta-lactoglobulin. Comparative sequence analysis of BLG-col to milk beta-lactoglobulin was carried out using CLUSTALW2 and a molecular model for BLG-col was constructed (PMDB ID-PM0076812). The synthesized variant pentapeptide (IIAMK, m/z-576 Da) was found to inhibit angiotensin I-converting enzyme (ACE) with an IC50 of 498 +/- 2 mu M, which was rationalized through docking simulations using Molgrow virtual docker. (C) 2012 Elsevier Masson SAS. All rights reserved.

Proteomic profiling of high glucose primed monocytes identifies cyclophilin A as a potential secretory marker of inflammation in type 2 diabetes

Hyperglycemia is widely recognized to be a potent stimulator of monocyte activity, which is a crucial event in the pathogenesis of atherosclerosis. We analyzed the monocyte proteome for potential markers that would enhance the ability to screen for early inflammatory status in Type 2 diabetes mellitus (T2DM), using proteomic technologies. Monocytic cells (THP-1) were primed with high glucose (HG), their protein profiles were analyzed using 2DE and the downregulated differentially expressed spots were identified using MALDI TOF/MS. We selected five proteins that were secretory in function with the help of bioinformatic programs. A predominantly downregulated protein identified as cyclophilin A (sequence coverage 98%) was further validated by immunoblotting experiments. The cellular mRNA levels of cyclophilin A in various HG-primed cells were studied using qRT-PCR assays and it was observed to decrease in a dose-dependent manner. LC-ESI-MS was used to identify this protein in the conditioned media of HG-primed cells and confirmed by Western blotting as well as ELISA. Cyclophilin A was also detected in the plasma of patients with diabetes. We conclude that cyclophilin A is secreted by monocytes in response to HG. Given the paracrine and autocrine actions of cyclophilin A, the secreted immunophilin could be significant for progression of atherosclerosis in type 2 diabetes. Our study also provides evidence that analysis of monocyte secretome is a viable strategy for identifying candidate plasma markers in diabetes.

SPARSE SIGNAL RECONSTRUCTION BASED ON SIGNAL DEPENDENT NON-UNIFORM SAMPLES

The classical approach to A/D conversion has been uniform sampling and we get perfect reconstruction for bandlimited signals by satisfying the Nyquist Sampling Theorem. We propose a non-uniform sampling scheme based on level crossing (LC) time information. We show stable reconstruction of bandpass signals with correct scale factor and hence a unique reconstruction from only the non-uniform time information. For reconstruction from the level crossings we make use of the sparse reconstruction based optimization by constraining the bandpass signal to be sparse in its frequency content. While overdetermined system of equations is resorted to in the literature we use an undetermined approach along with sparse reconstruction formulation. We could get a reconstruction SNR > 20dB and perfect support recovery with probability close to 1, in noise-less case and with lower probability in the noisy case. Random picking of LC from different levels over the same limited signal duration and for the same length of information, is seen to be advantageous for reconstruction.

Random forest algorithm with derived geographical layers for improved classification of remote sensing data

Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. The LC dynamics are being captured using multi-resolution remote sensing (RS) data with appropriate classification strategies. RS data with important environmental layers (either remotely acquired or derived from ground measurements) would however be more effective in addressing LC dynamics and associated changes. These ancillary layers provide additional information for delineating LC classes' decision boundaries compared to the conventional classification techniques. This communication ascertains the possibility of improved classification accuracy of RS data with ancillary and derived geographical layers such as vegetation index, temperature, digital elevation model (DEM), aspect, slope and texture. This has been implemented in three terrains of varying topography. The study would help in the selection of appropriate ancillary data depending on the terrain for better classified information.